Mapreduce自定义数据类型

Hadoop自带的数据类型：

Intwritable,LongWritable,Text,xxWritable.

 

某些情况下：使用自定义的数据类型方便一些（类似java中的pojo）。

实现：

实现writableComparable接口即可。

场景例如：

成绩表：由语文，数学，英文组成。

上传到hdfs上score目录下一个score.txt文件--文件内容如下：

想让按照总成绩进行排名。如果成绩相同，则按照语文，数学，英文来排序。

一、自定义ScoreWritable实现writableComparable接口：

package com.day07;

import org.apache.hadoop.io.WritableComparable;

import java.io.*;
public class ScoreWritable implements WritableComparable<ScoreWritable> {
    int chinese;
    int math;
    int english;
    int sum;

    public ScoreWritable() {
    }

    public ScoreWritable(int chinese, int math, int english) {
        this.chinese = chinese;
        this.math = math;
        this.english = english;
        this.sum=chinese+english+math;
    }

    @Override
    public String toString() {
        return "ScoreWritable{" +
                "chinese=" + chinese +
                ", math=" + math +
                ", english=" + english +
                ", sum=" + sum +
                '}';
    }

    public int getChinese() {
        return chinese;
    }

    public void setChinese(int chinese) {
        this.chinese = chinese;
    }

    public int getMath() {
        return math;
    }

    public void setMath(int math) {
        this.math = math;
    }

    public int getEnglish() {
        return english;
    }

    public void setEnglish(int english) {
        this.english = english;
    }

    public int getSum() {
        return sum;
    }

    public void setSum(int sum) {
        this.sum = sum;
    }
    //比较
    public int compareTo(ScoreWritable that) {
        //先比较总成绩
        if (this.sum>that.getSum()){
            return -1;
        }else if(this.sum<that.getSum()){
            return 1;
        }else{
            if (this.chinese>that.getChinese()){
                return -1;
            }else if (this.chinese<that.getChinese()){
                return 1;
            }else {
                return -(this.math-that.getMath());
            }
        }
    }
    //序列化--dataOutput(data流)：可以自定义序列化对象，节省空间，hadoop用的就是这个流
    public void write(DataOutput out) throws IOException {
        out.writeInt(chinese);
        out.writeInt(math);
        out.writeInt(english);
        out.writeInt(sum);
    }
    //反序列化
    public void readFields(DataInput in) throws IOException {
        this.chinese = in.readInt();
        this.math = in.readInt();
        this.english = in.readInt();
        this.sum = in.readInt();
    }
}

注意：

最好实现toString方法。

 

二、编写ScoreJob类用于测试自定义的ScoreWritable

package com.day07;

import com.day03.MaxSaleJob;
import com.google.common.io.Resources;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.IOException;

public class ScoreJob {
    public static class ScoreMapper extends Mapper<LongWritable,Text,ScoreWritable,NullWritable>{
        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            //super.map(key, value, context);
            String[] grades = value.toString().split(",");
            ScoreWritable score = new ScoreWritable(Integer.parseInt(grades[0]), Integer.parseInt(grades[1]), Integer.parseInt(grades[2]));
            context.write(score,NullWritable.get());
        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {



        Configuration coreSiteConf = new Configuration();

        coreSiteConf.addResource(Resources.getResource("core-site-local.xml"));
        //设置一个任务
        Job job = Job.getInstance(coreSiteConf, "score");
        //设置job的运行类
        job.setJarByClass(ScoreJob.class);
        //mrdemo/target/mrdemo-1.0-SNAPSHOT.jar
        //job.setJar("mrdemo/target/mrdemo-1.0-SNAPSHOT.jar");
        //设置Map和Reduce处理类
        job.setMapperClass(ScoreMapper.class);
        //map输出类型
        job.setMapOutputKeyClass(ScoreWritable.class);
        job.setMapOutputValueClass(NullWritable.class);
        //设置job/reduce输出类型
        /*job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(NullWritable.class);*/

        //设置任务的输入路径
        FileInputFormat.addInputPath(job, new Path("/score/"));
        FileSystem fileSystem = FileSystem.get(coreSiteConf);
        if(fileSystem.exists(new Path("/out/"))){
            fileSystem.delete(new Path("/out/"),true);
        };

        FileOutputFormat.setOutputPath(job, new Path("/out/"));
        //运行任务
        boolean flag = job.waitForCompletion(true);

        if(flag){
            FSDataInputStream open = fileSystem.open(new Path("/out/part-r-00000"));
            byte[] buffer = new byte[1024];
            IOUtils.readFully(open,buffer,0,open.available());
            System.out.println(new String(buffer));
        }
    }
}

三、测试结果，类似于一下内容